Stereo Vision
xtan explores stereo vision systems where multi-camera geometry, spatial tracking, and deterministic sensing enable reliable depth perception and real-world spatial analysis.
Depth perception through camera geometry
Stereo vision systems estimate depth by analyzing the difference between two or more synchronized camera views. These systems are widely used in robotics, spatial perception, machine vision, and environment mapping. Geometry-aware pipelines may support accurate spatial reconstruction and motion analysis.
Potential for robotics and spatial computing
Stereo vision is commonly used in robotics, autonomous systems, XR environments, and machine perception. Multi-view sensing may support workflows where depth estimation and spatial awareness contribute to environment understanding and interactive systems.
Why xtan can be relevant
xtan focuses on stereo vision, geometry-first interaction, and practical spatial systems. Within stereo vision environments this may support experimental perception pipelines, spatial tracking systems, and research into geometry-based depth sensing.